A Survey on Wind Turbine Condition Monitoring and Fault Diagnosis—Part II: Signals and Signal Processing Methods

By Wei Qiao, Dingguo Lu. IEEE transactions on industrial electronics (1982. Print), 2015

373 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/bf0538131a57ef8a42c74afef6204e7756513401

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Dong Yang
2. Weiting Zhang
3. Yaguo Lei
4. Hongchao Wang

In Control and Systems Engineering

1. Yaguo Lei
2. Jing Lin
3. Dong Yang
4. Weiting Zhang
5. Hongchao Wang
6. Feng Jia
7. Jun Yan
8. Steven X. Ding

Citations in the corpus

• Mel Frequency Cepstral Coefficient and its Applications: A Review (2022, background): “The turbine plays a vital role in converting power and many application tools have been developed for monitoring the turbine [173].”
• Data-Driven Methods for Predictive Maintenance of Industrial Equipment: A Survey (2019, background): “mine the best time for the implementation of the maintenance strategy [42]–[44].”
• Multiscale Convolutional Neural Networks for Fault Diagnosis of Wind Turbine Gearbox (2019, background): “Therefore, condition monitoring and fault diagnosis of WT gearbox have gained considerable attentions from both academia and industry [4]–[8].”
• An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data (2016, background): “In modern industries, machines have become more automatic, precise, and efficient than ever before [6]–[8], which”